Forensic analysis involves the observation and identification of an object that may exist in part or in its entirety on some sort of supporting surface. This analysis typically compares the sample in question to other possible reference samples or reference data to make an association that relates it to a specific person, place or event. Forensic analysis is widely used in law enforcement or legal disputes as evidence in a range of situations from homicide to fraud. More specifically, the goal is usually to provide evidence of the existence of a direct link, for example, between a suspect and a crime scene, a victim and a suspect, a weapon and a suspect, etc. To do so with a high degree of specificity and discrimination from possible variations of the sample is essential. Examples of forensic samples include, but are not limited to, fingerprints, gunshot residues, condom lubricants, multi-layer paint chips, fibers, ink samples and thin layer chromatography plates.
The quality of a forensic analysis is critical in making the association of evidence as unambiguous as possible, thereby providing compelling identifications and linkages. In many cases, such as with fingerprints, this identification has widely accepted requirements where as in others, such as fiber characterization and comparison, the uniqueness of the results can be disputed. Even the most unique and definitive identification of biological evidence based on genetic information has been successfully questioned and removed as compelling evidence. Minimizing the subjective components or features of a forensic analysis to make compelling identifications and linkages therefore becomes a critical aspect of all forensic analysis. Doing so quickly and in a cost effective manner is equally important.
In most legal cases, the ability of a jury or judge to understand the forensic evidence, and the ability of the scientist to convey its value determines the utility of the forensic method. As a result, methods which allow the objects to be visually compared or which show simple representations of the item under scrutiny are the most widely accepted and understood by non-specialists. Despite the existence of many advanced scientific techniques and analysis methods that are very sophisticated, many such techniques may not be understood by non-specialists, and may thereby raise some doubts as to its validity. Visual forensic analysis and visual comparisons are amongst the most widely accepted forensic methods used to date.
Advances in science and technology have enabled many new approaches to sample analysis, bringing forensic science into an era which goes far beyond the classic perception of an investigator looking thru a magnifying glass for small traces of evidence. Numerous techniques exist that allow detailed chemical and elemental identification. This includes most all analytical chemistry methods, such as mass spectroscopy, x-ray analysis, scanning electron microscopy and chromatography, that are widely used today to characterize gaseous, liquid and solid materials. Many of these methods are extremely sensitive and require finite material for their use that is consumed as part of the analysis process. Advances in the sensitivity of analytical chemistry methods and instruments over the years have reduced this problem but these methods are still not considered non-destructive. This becomes increasingly important as smaller and smaller pieces of pieces of evidence are examined and required in forensic analysis.
Spectroscopic imaging combines digital imaging and molecular spectroscopy techniques, which can include Raman scattering, fluorescence, photoluminescence, ultraviolet, visible and infrared absorption spectroscopies. When applied to the chemical analysis of materials, spectroscopic imaging is commonly referred to as chemical imaging. Instruments for performing spectroscopic (i.e. chemical) imaging typically comprise an illumination source, image gathering optics, focal plane array imaging detectors and imaging spectrometers.
In general, the sample size determines the choice of image gathering optic. For example, a microscope is typically employed for the analysis of sub micron to millimeter spatial dimension samples. For larger objects, in the range of millimeter to meter dimensions, macro lens optics are appropriate. For samples located within relatively inaccessible environments, flexible fiberscope or rigid borescopes can be employed. For very large scale objects, such as planetary objects, telescopes are appropriate image gathering optics.
For detection of images formed by the various optical systems, two-dimensional, imaging focal plane array (FPA) detectors are typically employed. The choice of FPA detector is governed by the spectroscopic technique employed to characterize the sample of interest. For example, silicon (Si) charge-coupled device (CCD) detectors or CMOS detectors are typically employed with visible wavelength fluorescence and Raman spectroscopic imaging systems, while indium gallium arsenide (InGaAs) FPA detectors are typically employed with near-infrared spectroscopic imaging systems.
Spectroscopic imaging of a sample can be implemented by one of two methods. First, a point-source illumination can be provided on the sample to measure the spectra at each point of the illuminated area. Second, spectra can be collected over the an entire area encompassing the sample simultaneously using an electronically tunable optical imaging filter such as an acousto-optic tunable filter (AOTF) or a liquid crystal tunable filter (“LCTF”). Here, the organic material in such optical filters are actively aligned by applied voltages to produce the desired bandpass and transmission function. The spectra obtained for each pixel of such an image thereby forms a complex data set referred to as a hyperspectral image which contains the intensity values at numerous wavelengths or the wavelength dependence of each pixel element in this image.
Currently there exists a need for accurately analyzing documents for latent fingerprints. There exists a need for a system and method to analyze a number of documents, detect latent fingerprints, and associate these latent fingerprints with an individual.